# python-tensorflowHow do I concatenate tensorflow objects in Python?

Concatenating tensorflow objects in Python is a process of combining multiple tensors into a single tensor. This can be done using the `tf.concat`

function.

The `tf.concat`

function takes in a list of tensors and a dimension value as parameters. The tensors in the list are then combined along the dimension specified.

## Example code

```
# Create two tensors
x = tf.constant([[1, 2], [3, 4]])
y = tf.constant([[5, 6], [7, 8]])
# Concatenate the two tensors along axis 0
concat_0 = tf.concat([x, y], 0)
# Concatenate the two tensors along axis 1
concat_1 = tf.concat([x, y], 1)
# Output
print("Concatenation along axis 0: \n", concat_0)
print("Concatenation along axis 1: \n", concat_1)
```

## Output example

```
Concatenation along axis 0:
tf.Tensor(
[[1 2]
[3 4]
[5 6]
[7 8]], shape=(4, 2), dtype=int32)
Concatenation along axis 1:
tf.Tensor(
[[1 2 5 6]
[3 4 7 8]], shape=(2, 4), dtype=int32)
```

## Code explanation

`tf.concat`

: This is the function used to concatenate tensors.`[x, y]`

: This is the list of tensors that are to be concatenated.`0`

/`1`

: This is the dimension along which the tensors are to be concatenated.

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